Intended Use

For viewing, post-processing, and quantitative evaluation of cardiovascular Magnetic Resonance (MR) images in a DICOM Standard format, validated for adult patients.

Technology

Software uses user inputs, standard algorithms, and automated deep learning detection algorithms to perform visualization, segmentation, cardiac function analyses (ejection fraction, myocardial mass, thickness, diastolic function), 2D flow studies, and integrates with PACS and HL7 servers.

Performance

QIR Suite underwent extensive verification and validation including unit tests, software integration and verification tests, clinical evaluation by physicians. Performance was compared to predicate devices using patient MR datasets from multiple vendors and field strengths, showing high correlation (>0.97) and low mean differences (<10%) in quantitative measurements. Deep learning segmentation algorithms achieved Dice coefficients around 0.89 to 0.91, comparable to published results. No new clinical studies were required.

Predicate Devices

No predicate devices specified

Device Timeline

  • 1

    Submission

    5/25/2021

    1 year, 4 months
  • 2

    FDA Approval

    9/30/2022

Ready to Sharpen Your Edge?

Join hundreds of your peers who rely on RadAI Slice. Get the essential weekly briefing that empowers you to navigate the future of radiology.

We respect your privacy. Unsubscribe at any time.